Within the Remote Sensing and Geoinformatics group at FU Berlin, we have a research focus on vegetation remote sensing. We are interested in exploring how we can use remotely sensed information to characterize and quantify grasslands and forests to support the management of natural and managed ecosystems and to better understand ecological processes.

For this we make use of data from a variety of (mostly optical) sensor systems including multi-, and hyperspectral satellite data as well as airborne and terrestrial laserscanning and aerial imagery. Current application fields include the development of work-flows to inventory the biomass of forests with an additional focus on understorey elements which act as important driver of wildfires. We furthermore focus on the development of remote sensing workflows that allow to map and characterize urban trees and other vegetation types to improve our understanding of the type and the quantity of ecosystem services and disservices provided by urban greenery.

Methodologically, we have a focus on the application of methods from the field of artificial intelligence, particularly machine learning and deep learning.